Power Control Algorithms for Media Transmission in Remote Healthcare Systems

• Published in: IEEE access Vol. 6; no. 2018; pp. 42384 - 42393
• Main Authors: Sodhro, Ali Hassan, Pirbhulal, Sandeep, Qaraqe, Marwa, Lohano, Sonia, Sodhro, Gul Hassan, Junejo, Naveed Ur Rehman, Luo, Zongwei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: adaptive; Algorithms; Body area networks; Control algorithms; Energy consumption; Energy efficiency; energy-efficient; Health care; Healthcare systems; Heuristic algorithms; Industrial plants; Media; medical media; Medical services; Portable equipment; Power control; Power management; Reliability; Wearable technology; Wireless sensor networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2859205

Currently, medical media technologies have become a center of attention due to emerging trends in miniaturized wearable devices from factories to health corner stores everywhere. Due to the power-constrained nature of these portable devices, it is challenging to adopt them during critical medical operations and diagnoses. Maximizing energy efficiency and, hence, extending the battery life is vital. In addition, conventional approaches with constant transmission power are inappropriate option for green and smart healthcare. Thus, this paper first proposes a transmission power control (TPC)-based energy-efficient algorithm (EEA) for when a subject is in different postures, i.e., standing, walking, and running, in wireless body sensor networks. Second, a hardware platform was developed on the Intel Galileo board to test and compare the proposed EEA and conventional adaptive TPC (ATPC) in terms of energy and channel reliability or packet loss ratio (PLR). Experimental results revealed that the proposed EEA obtained energy savings of 42.5% with an acceptable PLR compared with that of the traditional ATPC method.